If we know the distribution of \(y|x\) , Eqn (REF ) can be modified using Bayes' rule to sample from the posterior distribution \(p(x|y)\) , and this procedure has been successful in inverse problems such as compressed sensing MRI. We emphasize that during training, the score model is agnostic to the MRI forward model, which enhances its robustness to forward model shifts when applied to inverse problems [1]}.
